An adaptive spectrum sensing architecture for dynamic spectrum access networks

Dynamic spectrum access networks are expected to operate in a manner that is transparent to the incumbent licensed spectrum users. Conventional non-adaptive wideband spectrum sensing approaches could potentially be inefficient since they employ the same scanning resolution to track signals, even though different signals require spectrum scans with different sensing parameters. In this paper, we present an adaptive spectrum sensing framework that varies its parameters according to the characteristics of the spectrum of interest. Furthermore, we propose a dynamic scheduling algorithm for spectrum sensing that can be implemented in both a conservative and non-conservative manner. This algorithm allocates different time resolutions to several portions of spectrum using a backoff mechanism. The proposed algorithm has been employed to perform the 'listenbefore- talk' function of a cognitive radio, and performance results have been obtained with respect to the improvement in the sensing efficiency over a non-adaptive approach, secondary spectrum utilization, and interference rate.